方法证据记录
Graph Neural Network
A Graph Neural Network (GNN) is a deep learning method, popularised by Kipf and Welling in 2017 with the Graph Convolutional Network, that learns from the relationships in network (graph) structures made of nodes and edges. It is designed for data that is naturally relational, such as social networks, molecular structures, and recommendation systems.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Graph Neural Network (GNN)
分类方法记录 · ml-model / deep-learning
- Kipf, T.N. & Welling, M. (2017). Semi-Supervised Classification with Graph Convolutional Networks. ICLR. · URL
- Veličković, P. et al. (2018). Graph Attention Networks. ICLR. · URL
- Hamilton, W.L. (2020). Graph Representation Learning. Morgan & Claypool. · DOI 10.1007/978-3-031-01588-5
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